Download Neuronal Activity in the Hippocampus During Delayed Non

HIPPOCAMPUS, VOL. 2, NO. 3, PAGES 323-3349 JULY 1992
Neuronal Activity in the Hippocampus During Delayed
Non-Match to Sample Performance in Rats:
Evidence for Hippocampal Processing
in Recognition Memory
Tim Otto and Howard Eichenbaum
Department of Psychology, University of North Carolina a t Chapel Hill,
Chapel Hill, NC U.S.A.
ABSTRACT
Neuronal activity in the CAI of rats was explored with regard to functional correlates of
performance in an odor-guided continuous delayed non-match to sample task. Although different
CAI cells fired in association with each identifiable trial event, these analyses focused on cells
that fired selectively during the period of odor cue sampling and response generation. The firing
patterns of many of these cells reflected the match or non-match comparison between current
and previous odor cues independent of the particular stimuli that composed those comparisons.
Such cells were more prevalent in sessions when performance was highly accurate. Hippocampal
cells did not demonstrate stimulus-evoked firing that persisted through the memory delay, nor
did they fire differentially to session-novel vs. repeated odor presentations. These results suggest
that the hippocampus contributes to recognition memory by processing comparisons between
current information and representations of previous stimuli stored in parahippocampal and neocortical structures.
Key words: hippocampus, learning, memory, recognition
The delayed non-match to sample (DNMS) task has been cluding Ammon’s horn, dentate gyrus, and subicular coma particularly fruitful behavioral paradigm for exploring the plex) was critical for recognition memory (cf. Scoville and
role of the hippocampal system in memory. This task was Milner, 1957; Mishkin, 1978), but the results of recent exoriginally created to assess visual recognition memory in periments have suggested that this conclusion may have been
monkeys by exploiting their natural preference for a novel premature. In nearly all studies on primates, surgical ablation
object over another object presented a few seconds or min- of the hippocampus was accompanied by significant damage
utes earlier (Gaffan, 1974; Mishkin and Delacour, 1975). The to the surrounding parahippocampal areas (including penDNMS task has played a central role in the development of rhinal, parahippocampal, and entorhinal cortex) and selective
a nonhuman primate model of the recognition memory im- removal of some or all of these cortical areas resulted in a
pairment that follows medial temporal lobe damage system greater deficit in DNMS than hippocampal ablation sparing
in humans (Gaffan, 1974; Mishkin, 1978). Confirming the va- part of the surrounding cortex (Murray and Mishkin, 1986;
lidity of this model, human amnesics are severely impaired Zola-Morgan et al., 1989a). These findings have brought into
in tasks similar to those created for monkeys (Aggleton et question the role of the hippocampus itself in recognition
al., 1988; Squire et al., 1988). Furthermore, the DNMS par- memory, suggesting that the parahippocampal cortical areas
adigm has been exploited very successfully in delineating might be the more critical structures supporting DNMS perwhich components of the medial temporal lobe are critical to formance. Nevertheless, substantial damage to the hipporecognition memory (cf. Squire and Zola-Morgan, 1991), and campus or fornix (which subserves hippocampal-subcortical
the paradigm has recently been successfully extended to stud- connections) that spares most of the parahippocampal areas
ies of recognition memory in rodents (Aggleton et al., 1986; and their neocortical connections results in significant deficits
Mumby et al., 1990; Rothblat and Kromer, 1991; Otto and on DNMS performance, at long memory intervals, indicating
that the hippocampus itself contributes to recognition memEichenbaum, 1992).
Initially it was assumed that the hippocampus itself (in- ory (cf. Gaffan, 1974; Zola-Morgan et al., 1989b; Clower et
al., 1991; Squire and Zola-Morgan, 1991).
Experimental data from recent studies on rats are consisCorrespondence and reprint requests to Dr. T. Otto, Department of
Psychology, University of North Carolina, CB #3270 Davie Hall, tent with the data from monkeys and further address the quesChapel Hill, NC 27599.
tion of whether the hippocampus is critical to recognition
323
324
HZPPOCAMPUS VOL. 2, NO. 3, JULY 1992
memory for nonspatial cues in nonprimates. Hippocampal ablation, fornix transection, or damage to parahippocampal
areas results in severe impairment in many spatial learning
and memory tasks (O’Keefe and Nadel, 1978) and certain
types of discrimination and a variety of complex learning
tasks (Eichenbaum et al., 1992a; 1992b). However, selective
aspiration of the hippocampus does not produce an impairment in object-cued DNMS tasks in rats (Aggleton et al.,
1986; Rothblat and Kromer, 1991). Furthermore, we recently
found that performance on an odor-guided delayed nonmatching task was impaired by perirhinal-entorhinal cortex
lesions but not by fornix transection (Otto and Eichenbaum,
1992). This pattern of results led us to suggest that parahippocampal areas may be sufficient to support recognition
memory across intermediate delays by maintaining a persistent hippocampal-independent memory trace for recent stimuli (Eichenbaum et al., 1992b; Otto and Eichenbaum, 1992).
Characterizations of neuronal activity in the medial temporal area in monkeys and rats performing recognition memory tasks have also led several investigators to conclude that
neocortical and parahippocampal cortical areas may play a
greater role than the hippocampus in recognition memory.
These studies have focused on two types of neural activity
patterns that might reflect short-term storage of a stimulus
trace. In some studies stimulus-evoked neural responses have
been observed to be greater for the presentation of novel stimuli than familiar ones, possibly reflecting a decreased requirement for reactivation of a persistent memory trace (cf.
Squire et al., 1992). In other studies, stimulus-evoked neural
activity has been observed to persist over the memory delay,
possibly reflecting a sustained activation of a perceptual representation (e.g., Fuster and Jervey, 1981). Each of these
putative memory-related activity patterns has been observed
in either neocortical or parahippocampal areas, but not in the
hippocampus. Brown and colleagues (Brown et al., 1987; Wilson et al., 1990; Riches et al., 1991) found that neurons in
parahippocampal cortical areas fired differentially to novel,
as opposed to familiar, visual stimuli, but cells in the hippocampus did not. The only observation of differential responses of hippocampal neurons to novel stimuli involves
conjunctions of visual and spatial cues (Rolls et al., 1989).
Furthermore, increased unit activity initiated by memory
cues and persisting through the delay period is prevalent in
the prefrontal (e.g., Goldman-Rakic, 1990), inferotemporal
(Fuster and Jervey, 1981; Miyashita and Chang, 1988), and
auditory (Sakurai, I990b) cortex, but no studies have reported cue-elicited, persistent delay activity or differential
activity for novel stimuli in hippocampal neurons of monkeys
or rats (e.g., Watanabe and Niki, 1985; Sakurai, 1990a).
Following the success of the DNMS task in studies of amnesia in primates, we have pursued the development of a similar paradigm for both neuropsychological and neurophysiological studies of hippocampal function in rats. Exploiting
their superb capacities in olfactory learning, we have created
an odor-guided, continuous delayed non-matching (cDNM)
task that intact rats acquire rapidly and in which performance
can be manipulated by varying the memory delay requirement
or the level of interitem interference (Otto and Eichenbaum,
1992). This report focuses on the activity of putative principal
neurons in hippocampal area CA1 of rats during performance
of the odor-cued cDNM task. Post hoc analyses were used
to characterize the functional correlates of these cells in relation to stimulus analysis, retention during the memory delay
period, and behavioral responses. Our conclusion, consistent
with the data from previous studies on visual and auditory
delayed matching tasks in monkeys and rats, is that the hippocampus actively participates in recognition memory processes by matching current sensory information to representations of recently presented stimuli stored in
parahippocampal and neocortical areas.
METHODS
Subjects
A total of 16 male Long-Evans rats weighing approximately
325 g at the time of surgery completed the training and recording regimen presented below. Animals were maintained
on a 12: 12 hour 1ight:dark cycle in an environmentally controlled room. All behavioral training was conducted during
the light cycle. Food was available ad libitum; water access
was restricted to a 20-minute period at the end of each day
following training.
Electrodes and surgery
Rats were tranquilized with acepromazine (10 mgkg IM),
anesthetized with pentobarbital (40 mg/kg i.p.), and given
atropine (0.5 mgikg IM) to reduce excess salivation. The head
was placed in a stereotaxic frame with bregma and lambda
level. Using aseptic procedures, the scalp was resected and
burr holes were drilled in the skull for implantation of four
stainless steel screws including one in the frontal bone that
also served as the electrical ground. An additional burr hole
was drilled at 3.2 mm posterior to and 1.8 mm lateral to
bregma on the right side. The electrode consisted of a microwire bundle constructed with 10 25 pm Formvar-insulated
nichrome wires threaded through a 26-gauge cannula and cut
to equal lengths (Eichenbaum et al., 1977). This was attached
to a vertically driveable connector assembly (Kubie, 1984)
and implanted so that the electrode tips were 1-1 .S mm below
the pial surface. The electrode was advanced in 80 bm steps
separated by 4-24 hour settling periods until cellular activity
was identified. The water deprivation schedule and training
resumed after a 4-7 day recovery.
Recording and data acquisition
Unit activity recordings were passed initially through a
multichannel unity gain JFET preamplifier for impedance
matching. All 10 unit channels were recorded simultaneously
using a multichannel differential-amplifier and spike amplitude window discriminator system. A unit channel that had
no detectable unit activity and normal background noise level
was selected to be the differential reference. Differential activity on each channel was amplified 10,000x and filtered at
300-5,000 Hz, then passed to a separate window discriminator channel. In cases where two, or occasionally three,
units could be discriminated on the same channel by visual
inspection of the monitor, the amplifier output was passed to
multiple window channels for unit separation. Only units with
signal-to-noise greater than 2.5: 1 and with firing rate and
HIPPOCAMPUS AND DELAYED NON-MATCH TO SAMPLE / Otto and Eichenbaum
spike width characteristics of complex spike cells (Ranck,
1973) were used. The accuracy of unit isolation was assessed
continuously throughout the recording session by comparing
the trigger signal of window detection to a display of each
action potential waveform and to the waveform of other
saved spikes. To eliminate electrical artifacts, recordings
from a separate unit channel with no detectable unit spikes
were passed to a window set with the low threshold just above
background noise and no high threshold; all spike events
within 100 ms of identified “noise” were ignored in post hoc
analyses. When more than five noise events were detected
in a trial, the entire trial was eliminated from the analysis.
Spike and behavioral events were passed to a sample-andhold interface that was read and reset at 1,000 Hz by interrupt
software operating in the background of the behavioral control programs running on a DEC microVax computer.
Behavioral apparatus
All behavioral training and recording took place in a 30 cm
square aluminum chamber with walls slanted at 15” outward
from the base. On one wall of the chamber a 2.5 cm sniff port
with conical airstream inlet was centered 5 cm above the
floor, and a 1 cm circular water port was centered on a horizontal shelf located 1 cm above the sniff port. Responses to
the sniff and water ports were monitored by separate infrared
photoelectric cells. Two 24 V house lights were mounted beside the sniff and water ports at a height of 13 cm from the
floor. Odor cues were presented as required using a 16-channel flow-dilution olfactometer. Stimulus odors consisted of
dilute solutions of various volatile chemicals diluted further
as follows. A clean airstream flowed continuously at a rate
of 0.5 L h i n ; an odor-saturated airstream was added at 0.5
L/min to the clean airstream when appropriate, resulting in
a final flowrate of 1.0 L/min. Odorized or clean airstreams
were passed through a three-way solenoid valve mounted just
outside the behavioral chamber. During the intertrial interval
(the delay) the airstreams were diverted by this valve in its
deactivated state to a vacuum dump at 2 L/min. To present
an odor to the subject this solenoid valve was activated, allowing the odonzed airstream to reach the sniff port for specified periods. Since the vacuum dump flow rate was greater
than the olfactometer-generated airstream, odors in the sniff
port and chamber were effectively eliminated during periods
when no odor was being presented. Odors lingering within
the chamber were exhausted continuously by means of a fan
mounted at the top of the enclosure. All procedural events
were controlled and behavioral responses recorded by a microcomputer with custom-designed interfaces, as described
above.
Behavioral training procedure
Training on the cDNM task was accomplished in a series
of three phases. First, at the outset of two shaping sessions
rats were provided with two to five water reinforcers at the
water port. On each of 60 trials thereafter a 500 ms nose poke
into the sniff port resulted in the presentation of an odor chosen on a pseudorandom basis from among the set of 16. A
subsequent water port response terminated odor presentation
and was reinforced with 0.05 mL water. During these shaping
325
sessions, the odor presented always differed from the odor
used on the immediately preceding trial. A 3-second delay
was imposed between trials; the house lights were extinguished during the delay and were subsequently reilluminated
to signal the availability of the next trial. Nose pokes into the
sniff port during the last 2 seconds of the delay extended the
delay by an additional 2 seconds.
In the second stage, rats were trained on cDNM in 100 trial
daily sessions. The odor presented on half the trials was different from that used on the preceding trial (a non-match or
S + trial) and a “go” water port response ( R + ) was rewarded; on the other half of the trials the odor was the same
as that presented on the preceding trial (a match or S - trial)
and, since water port responses on these trials were not reinforced, the correct response was a “no go” to the water port
(R-). Errors of commission resulted in the immediate offset
of the house lights. On any trial when no water port response
was made within 5 seconds of odor onset, the odor and the
house lights were turned off simultaneously and the delay
began. Correct responses were followed by a 3-second delay:
incorrect responses were followed by a 7-second delay and,
after the incorrect responses on match trials, a correction
trial. Daily training continued until rats reached a criterion
of 18 correct responses out of 20 consecutive trials. This was
accomplished by all rats in two to three sessions.
In the third training stage, daily training sessions continued
while searching for and recording cells. During these sessions, the delay was held constant at 6 seconds regardless of
the response and correction trials following errors were not
employed. The actual delay between odor offset on one trial
and odor onset on the next could be somewhat longer, depending on the rat’s latency to initiate a trial following the
onset of the houselight signal. In addition, a variable (0, 300,
or 500 ms) delay was inserted between the nose poke into the
sniff port and odor onset, to permit differential synchronization of cellular activity to the behavioral act of initiating the
trial and the presentation of the sensory stimulus. The performance of subjects during the test period was variable,
ranging from 51% to 95% correct, and all errors involved incorrect “go” responses on match trials. On each day electrodes were surveyed for cellular activity prior to training. If
no cells were identified, a 100-trial session was presented to
maintain performance. When the activity of at least one cell
could be isolated, the electrodes were again surveyed and
cells were isolated during an initial 20-30 trial practice period.
A 95-250 trial recording and training session was then presented. After each session the electrode was advanced 80 pm.
Data analysis
Initial analyses were focused on determining whether
variations in unit activity could be related to events that occur
in every trial. These analyses exploited the repetitive nature
of the sequence of behavioral events that occurred on each
trial. The trial events that could be reliably identified were:
(1) onset of the house lights signaling the beginning of a trial;
( 2 ) entry into the sniff port initiating the trial; (3) onset of
odor presentation; (4) removal of the nose from the sniff port
(designated the “unpoke”); and (5) entry into the water port
as the discriminative response to retrieve the reward. Raster
displays and summary perievent histograms were constructed
326
HIPPOCAMPUS VOI,. 2, NO. 3, JULY 1992
to display the averaged, event-synchronized unit activity
from 2 seconds before until 2 seconds after each trial event.
Since each unit was recorded for many trials, it was possible
to test statistically whether unit activity increased reliably
during specific trial periods. Based on our previous analyses
of hippocampal complex spike cells in rats performing odor
discriminations (Eichenbaum et al., 1987; Wiener et al.,
198Y), we expected that cells with behavioral correlates in the
odor task would fall into two functional categories: cue-sampling cells that f i e maximally during the period between trial
initiation and the water port response, and goal-approach
cells of two subtypes, cells that fire maximally just before or
during the trial initiation (sniff port entry) and reward-approach cells that fire as the rat completes the approach to the
water cup nose poke and during reward consumption. Based
on these expectations, we developed analyses defining each
cell type by peak firing time and statistical criteria that tested
for reliably increased firing during the peak firing period.
With regard to the peak firing criterion, cue-sampling cells
were defined as those neurons whose average activity was
maximal between 100 ms after trial initiation and at least 100
ms before the water port response; trial initiate cells were
defined as those whose activity was maximal 500 ms before
to 100 ms after sniff port entry; and reward approach cells
were defined as those whose activity peaked 100 ms before
to 500 ms after entry into the water port. To perform the
statistical analyses, the background firing rate of a cell was
measured during the 1 second period preceding onset of the
house lights at the beginning of each trial. The firing rate
during the peak firing period defined by the events described
above were determined, and paired t-tests (two-tailed) were
carried out to determine whether the firing during these periods changed relative to background firing. For all units with
significant ( P < .05) increases in firing, a further series of
post hoc analyses was applied to test whether firing rates
increased preferentially during trials with specific stimulus
and response combinations as described below. In these
cases the firing rates during the same period of increased firing were compared between pairs of trial types using a t-test.
RESULTS
The activity of 261 cells was recorded and analyzed; 120
had statistically reliable behavioral correlates (Table 1). As
found in our previous studies on hippocampal neuronal activity in rats performing different types of odor discrimination
tasks (Eichenbaum et al., 1987; Wiener et al., 1989), there
were different CA1 cells with striking increases in firing associated with virtually every identifiable event occurring during performance of the cDNM task (Fig. 1). A total of 44 cells
(16.9%of the total, or 36.7% of cells with identified behavioral correlates) fired during odor sampling or water port responses. These cue-sampling and reward-approach cells are
the primary focus of this report, because they fire during periods associated with stimulus analysis and response generation. In addition, 50 cells increased firing during the memory
delay period. These cells, which were not categorized as cuesampling or reward-approach cells but potentially could bear
information relevant to recognition performance, were also
analyzed in detail.
Table 1. Categorization of Cells Recorded in Rats Performing
a Continuous Delayed Non-Match to Sample Task
Cell Type
No.
No.
% Total
Trial initiation
26
32
Cue-sampling
Strong matchhon-match
Weak matchhon-match
Response
Nonspecific
Unclassified
Reward approach
Matchhon-match
Nonspecific
Delay-related
N o behavioral correlate
50
141
Total
261
10.0%
12.3%
8
7
4
11
2
12
4.6%
6
6
19.2%
54.0%
Cue-sampling cells
While it may be presumed from their temporally selective
firing pattern that each of these cells is involved in some aspect of stimulus analysis or response generation, further observations and analyses indicate that subgroups of these cells
differentially contribute to odor-guided recognition memory
and that the activity patterns of most of these cells reflects
the demand for odor comparison in the cDNM task. While
the peak firing of cue-sampling cells occurs at various times
within the odor sampling period, maximal firing is best timelocked to one particular event. An example of this analysis
is presented in Figure 2. This cell’s activity was poorly locked
to the onset of the house lights or the odor, but partially synchronized to the initiation of odor sampling and sharply
locked to the cessation of odor sampling (the unpoke). We
found that some cells reached maximal firing rate relatively
soon after trial onset (Fig. IC), others had peak firing in the
middle of the odor sampling period (Fig. ID), and yet others
fire maximally just before the water port response (Fig. 1E).
Similarly, comparing events that best synchronized (i.e., produced the highest firing peak in a 100 ms bin) the activity of
each of the 3 2 cue-sampling cells, 13 were best synchronized
on trial initiation, 6 on odor onset, and 13 on the unpoke.
These data indicate that firing of relatively few cue-sampling
cells is best associated with simple sensory stimulation.
Rather, for the majority of cue-sampling cells, peak firing is
best time-locked to behavioral acts central to odor cue acquisition and to the matchlnon-match decision. No cue-sampling cell showed a striking specificity for a particular odor.
Histogram analyses comparing responses on trials with individual odors consistently revealed the nonspecificity of responses. In addition, inspection of the raster displays shown
in Figures 1-5 indicates that firing is not isolated to a small
fraction of the trials, as would be the case if these cells were
odor-selective.
Further statistical analyses were conducted to determine
whether cue-sampling cell f-iring reflected the matchhonmatch comparison between previous and current cues or
whether these cells could be better characterized as predicting the behavioral response. Initially, cellular activity at peak
firing periods was compared for all non-match (S +) versus
HIPPOCAMPUS AND DELAYED NON-MATCH TO SAMPLE / Otto and Eichenbaum
... - . . . .
. . . . . . . . ...
.~. _ . _
n=96
j l
E
B
*I
7
4
n = 144
327
n = 191
1Initiate
Ah
n = 243
F
C
Fig. 1. Examples of hippocampal CAl neurons whose activity is time-locked to different trial events. In this and all subsequent
figures, each panel includes a raster display of a block of approximately 30 representative trials (top) and a summary histogram
of activity within the entire session in spikeshec, accumulated in 100 ms bins (bottom). The number at the top right of each
histogram represents the total number of cDNM trials for which unit activity was recorded and summarized for that panel.
(A) A cell that fired maximally during the end of the memory delay. (B) A trial initiate cell that fired maximally just prior
to trial onset. Vertical tic marks to the right of the synch point indicate the occurrence of a water port response. (C-E) Cuesampling cells whose activity was maximal at different periods in the odor sampling period. (F) A reward-approach cell
whose activity was maximal just after completion of the water port response. In B, C, and D, vertical tic marks to the right
of the synch point indicate the occurrence of a water port response; in E and F , tic marks to the left of the synch point
indicate trial initiation.
all match ( S - ) trials using a two-tailed t-test. However, to
the extent that performance was accurate, differences in peak
firing on non-match ( S + ) trials match ( S - ) trials could be
attributable either to the matchhon-match distinction or the
difference in the associated response (R+ vs. R-). Fortunately, in most sessions there was a sufficient number of errors of commission (S-RS) to permit a direct comparison
of unit activity on non-match versus match trials where the
“go” ( R + ) behavioral response was constant. We therefore
categorized units as matchhon-match cells if there was a statistically significant ( p o s t hoc one-tailed) difference in mean
firing rate during the period of peak fiiing on S + R versus
S - R + trials. We also compared peak firing rates for these
cells on S + R + versus S - R - trials in further post hoc onetailed t-tests. For eight of these cells there was a significant
difference on all three comparisons; these cells will hereafter
be referred to as “strong” matchhon-match cells. An example of a strong non-match cell is provided in Figure 3. This
+
neuron fired maximally 300-500 ms after the unpoke (cessation of odor sampling) and prior to the water port response.
It fired quite strikingly (up to 13/s) on S + R + trials (Fig. 3A)
but fired at much lower rates during the same period on
S - R trials (Fig. 3B) and fired very little on S - R- trials
(Fig. 3C). Note that the latency to termination of odor sampling relative to trial initiation was roughly constant regardless of trial type; this was true of all matchhonmatch cells.
Of a total of eight strong matchhonmatch cells, seven preferred non-match trials and only one preferred match trials.
For the remaining matchhon-match cells the S + R + versus
S -R - comparison was not statistically significant; we will
refer to these as “weak” matchhon-match cells. Of a total
of seven of these cells five were weak non-match cells and
two were weak match cells.
For those cells where peak firing on S R and S - R
trials did not differ significantly, it is possible that their activity was better related to the type of response performed
+-
+ +
+
328
HIPPOCAMPUS VOL. 2, NO. 3, JULY 1992
. -. I. .: ,
. . . .
. . . .
. . . . .. ....
.
....
....
... . . .::......
. . .;..
.......
....
. . . . . . .
.......
. . . . . . I . . . .:..;
....
A
2
..*.
.I
n = 190
1
n
B
....
* ..
.. .. . . . ....
.. .:. . : :”.’.’;
. l
. . . .., . . . . ......... .
comparison, and were not further classified. The other 11 cuesampling cells did not fire differently across trial types and
so are classified here as nonspecific cue-sampling cells. An
example of a nonspecific cue-sampling cell is shown in Figure
5. This cell fired maximally in the middle of the odor sampling
period and its peak activity did not vary across trial types.
The absence of significant differences on these statistical tests
was not due to a lack of data from error ( S - R + ) trials. Indeed, we found that there was a higher error rate on sessions
in which these cells were recorded than on those in which
matchhon-match cells were observed. Two-tailed t-test comparisons revealed that performance accuracy associated with
nonspecific cue-sampling cells (62.9 ? 2.7% correct) was
lower than that associated with strong matchhon-match cells
(80.6 ? 2.6% correct; t = 4.6, df = 16, P < .01) or that for
all matchhon-match cells (74.6 k 2.6% correct; t = 2.9, df
= 23, P < .05).
Since recordings from parahippocampal and neocortical
neurons (and some experiments from hippocampal neurons)
have shown that some cells in these structures demonstrate
differential responses to novel vs. repeated stimuli, we compared the peak firing rates of cue-sampling cells on the first
presentation of each odor in a session with its second and
third presentations as an S stimulus. We restricted the comparisons to S + trials to eliminate matchhon-match effects
that might have overshadowed or artificially enhanced a novelty effect; this contingency resulted in comparing responses
+
..I.
..
.>
.
....
. . . . ..,... :.::
.* . .. .. ... . . .. . . . .
D .....
....
. . .. .. . . . . . .
:. : ..... . . . . . .......
... . .
:,.;.I
n
%. ,
I
..C..
Fig. 2. Example of differential synchronization of the activity
of a cue sampling cell to different trial events. This cell’s
activity was poorly synchronized to the onset of the house
lights (A) and to the onset of the odor cue (C), somewhat
synchronized to the trial initiation (B), and sharply timelocked to the cessation of odor sampling (the unpoke; D).
A
13
n =I22
S+R+
B
n
+
(R or R - ). In these cases one would expect a significant
difference in the S + R + versus S - R - comparison and, to
the extent that most responses are correct, a similar significant difference between S + and S- trials. This pattern of
peak firing rates was found for only four cells. Two of these
fired more on R + trials and two on R- trials. An example
of a response-predicting cell is presented in Figure 4. This
cell, like the strong non-match cell shown in Figure 3, fired
selectively during the period between the unpoke and the
water port response. However, unlike the non-match cell,
this cell fired at maximal rate on both S + R + and S - R +
trials and fired significantly less on S -R- trials.
Of the remaining 13 cue-sampling cells, 2 had too few trials
in which to assess firing in the critical S + R + versus S - R +
1
I
n = 81
S-Rn
Fig. 3. Example of a “strong” matchhonmatch cell that fired
sharply in association with the unpoke on correct non-match
trials (A), and fired at much lower rates during that period
on errors of commission (B), and on correct match trials ( C ) .
Vertical tic marks to the left of the synch point indicate the
time of trial initiation; tic marks to the right of the synch point
indicate the occurrence of a water port response.
HIPPOCAMPUS AND DELAYED NON-MATCH TO SAMPLE / Otto and Eichenbaum
A
n
n = 69
329
associated with the first stimulus presentation to those associated with stimulus repetitions greater than second or
third, so this strategy could only serve to inflate a potential
novelty effect. Despite this advantage none of the statistical
comparisons revealed a significant difference in peak firing
rate associated with first and later presentations of each odor.
Reward-approach cells
1
Even though the peak firing of reward-approach cells occurs just before and during reward consumption, these cells
could participate in matchhon-match processing associated
with feedback by reinforcement. We evaluated the association of activity in reward approach cells with match and nonmatch processing by comparing the mean peak activity on
S + R + versus S - R trials, thus directly assessing the effect
of recent stimulus presentations upon firing occumng well
after the end of odor sampling. Of a total 11 identified reward
approach cells, 3 fired disproportionately on match trials, 3
on non-match trials, and 6 fired equally on both trial types.
Two examples of reward approach cells are presented in Figure 6. The reward-approach non-match cell (Fig. 6A) fired
sharply immediately following execution of the water port
response on non-match trials but did not fire at this time on
match trials. The reward-approach match cell (Fig. 6B) had
the opposite pattern of activity, firing sharply just after the
water port response on match trials but not firing at this time
after non-match trials.
+
1
S-R-
fl
= 32
nn
-\Unpoke
n
Fig. 4. Example of a response-related cue-sampling cell that
fired sharply in association with the unpoke prior to the “go”
( R + ) response on both correct non-match trials (A) and errors of commission (B), but fired very little prior to R - responses associated with correct match trials (C). See Figure
3 legend for explanation of vertical tic marks to the left and
right of the synch point.
‘1 S+R+
fl
= 86
Delay-related neural activity
A large fraction of CA1 cells fired selectively at various
times during the delay period and, conversely, were inactive
during trial initiation, cue sampling, and response generation.
An example of one of these cells is shown in Figure 1A. None
of these cells increased firing during the period when the odor
was presented to the rat and each of these cells ceased firing
before onset of the succeeding trial. Furthermore, delay-related firing did not predict performance in the succeeding
trial. To test this we compared the activity of 31 cells for 1
second preceding correct vs. incorrect trials; in only 4 was
differential activity between correct and incorrect trials observed, for 2 of these increased activity was associated with
correct trials, and for the other 2 increased activity was associated with incorrect trials.
DISCUSSION
IUnpoke
Fig. 5. Example of a nonspecific cue-sampling cell that fired
equally strongly during the odor sampling period on all trial
types. See Figure 3 legend for explanation of vertical tic
marks to the left and right of the synch point.
The three main results of this experiment can be summarized as follows. (1) The firing of a large fraction of CA1
neurons fired was selectively associated with specific trial
events during cDNM performance. Combining the data
across different cells, the periods of increased hippocampal
unit activity spanned each cDNM trial. (2) The increased activity of the majority of cue-sampling cells was most tightly
time-locked to the active initiation or termination of odor
sampling. Approximately half of these cells fired differentially on match vs. non-match trials. Furthermore, the activity of these cells best reflects the matchhon-match comparison when cDNM performance accuracy is high. (3) While
some CAI cells were selectively active during the delay period, the firing poorly predicted performance on the suc-
330
HZPPOCAMPUS VOL. 2, NO. 3, JULY 1992
A
2
5
S+
1 sI
si
n=77
n = 51
1
I
n
Response
s-
n=72
rl
A1
n = 21
-\Response
Fig. 6. Examples of two reward-approach cells. (A) A cell that fired sharply during the water port response on non-match
trials (top) but not on match trials (bottom). (B) A cell that fired sharply during the water port response on match trials
(bottom) but not on non-match trials (top).
ceeding trial. Also, hippocampal cells did not fire differentially on the first vs. successive presentations of individual
odors. These findings suggest that CAI cells did not maintain
an active representation of the odor cue during the memory
delay. In the following sections, our findings are compared
to those from related reports, and our conclusions are discussed in terms of their implications for hippocampal processing in recognition memory.
Different hippocampal cells fire during each
trial event
Virtually all studies on hippocampal neuronal activity in
behaving animals report that every identifiable behavioral
event is associated with increases in the activity of at least
some neurons. Whether or not that behavior is critical to successful task performance, and whether or not performance
of the related behaviors depends on the integrity of the hippocampus. This observation has been interpreted in at least
two ways. First, some have suggested that this observation
merely reflects the variety of inputs constantly impinging on
hippocampal neurons. Second, others, including ourselves,
interpret this activity as a reflection of hippocampal processing and representation of all significant events whether
or not the task demands require use of that representation
(Eichenbaum and Cohen, 1988; Eichenbaum et al., 1992a).
Hippocampal processing reflects the outcome of
comparisons between current and stored
representations during recognition performance
While the activity of hippocampal cells is strongly influenced by both sensory inputs and ongoing behavioral output,
a close examination of the evidence indicates that the hippocampus is not involved in either perceptual or motor information processing per se. With regard to perceptual processing, hippocampal neuronal activity is strongly influenced
by particular visual, auditory, or olfactory cues, but a careful
analysis of the findings indicates that the hippocampus is not
merely a further stage of sensory processing. Rather, several
lines of evidence indicate that hippocampal neurons encode
combinations or conjunctions of stimuli when these cues define a specific spatial or temporal relationship. For example,
in our own studies of the same population of cells in rats
performing odor discrimination tasks, we found CA1 cuesampling cells that fired selectively in association with particular spatial configurations of odors during simultaneous
discrimination (Wiener et al., 1989). Other studies in rats
(Wible et al., 1986) and monkeys (Cahusac eta]., 1989; Rolls
et al., 1989; Ono et al., 1991) have also demonstrated hippocampal unit activity related to specific combinations of
stimuli and their spatial positions. Furthermore, in the widely
reported observation that hippocampal units fire in association with a rats’ spatial location, such “place fields’’ are defined by the spatial relations among multiple visual and nonvisual cues (O’Keefe and Conway, 1978; Muller and Kubie,
1987).
We have also previously observed that some hippocampal
cells fire in association with the sequences of cues presented
during successive odor discrimination (Eichenbaum et al.,
1987). The dependence of CA1 unit activity on the sequence
of discriminative cues has also been observed in rats performing a successive auditory discrimination task (Foster et
al., 1986). This finding may be related to the present and other
reports (Sakurai, 1990; Riches et al., 1991; Brown, 1982) of
matchhon-match correlates of CAl cellular activity in recognition memory tasks. Even though direct comparison between successively presented stimuli is not required to perform sensory discrimination tasks, the observation of strong
sequential dependencies indicates that the hippocampus processes comparisons among relevant stimuli. In addition, other
reports have described hippocampal coding of particular configurations of stimuli and behavioral responses in conditional
learning tasks (Cahusac and Miyashita, 1988; Miyashita et
al., 1989). Combining these findings, we have suggested that
HIPPOCAMPUS AND DELAYED NON-MATCH TO SAMPLE / Otto and Eichenbaum
the hippocampus participates in an encoding of critical relations among cues in all sorts of situations (Eichenbaum and
Cohen, 1988; Eichenbaum et al., 1992a; 1992b).
Further analyses of these findings indicate that what the
hippocampus encodes may not include the perceptual qualities of a particular combination of stimuli but, rather, an abstraction of the relevant relations among those stimuli. In the
present study, cells active during stihulus sampling did not
fire selectively during the presentation of a particular odor
or a small subset of odors. While the activity of many of these
cells depended on both previous and current stimuli, their
firing was dependent only on the outcome of the match or
non-match and not on the particular perceptual qualities upon
which the comparison was based. That matchinon-match correlates were most pronounced when performance was accurate suggests that this extraction of information by the hippocampus might be critical to behavioral decisions. Our
conclusion that hippocampal cellular activity reflects the abstraction of relations among cues is consistent with similar
descriptions of matchinon-match cells in other studies on recognition memory tasks in rats (Sakurai, 1990) and monkeys
(Riches et al., 1991), and the finding that spatial activity of
hippocampal units does not depend on the immediate presence of any particular cue but rather on the overall spatial
representation (O’Keefe and Conway, 1978; O’Keefe and
Speakman, 1987; Quirk et al., 1990). In addition, individual
hippocampal neurons may have highly specific yet quite different functional correlates when their activity is observed
across behavioral paradigms (Cahusac et al., 1989; Wiener et
al., 1989), consistent with our view that the activity of hippocampal cells is not determined by a particular combination
of stimuli but rather reflects abstract relations among cues
and events.
With regard to motor information processing, several investigations have demonstrated prominent activity of hippocampal neurons in relation to conditional or voluntary
motor responses in monkeys (Cahusac and Miyashita, 1988;
Cahusac et al., 1989; Miyashita et al., 1989; Wilson et al.,
1990), rabbits (Berger et al., 1976), rats (Sakurai, 1990a), and
humans (Halgren et al., 1978; Halgren, 1991). In our own
studies on odor discrimination and in this experiment, many
cells fired preferentially during task-related movements. Furthermore, at least in some situations, spatial correlates of
hippocampal unit activity are dependent on movement speed
and direction (Wiener et a]., 1989). However, in nearly all of
these cases, the particular movements associated with cellular activity could be directly related to other perceptual
events or reinforcements. For example, among those sessions
where performance was accurate in the present study, most
cue-sampling cells fired time-locked to behavioral acts involved in the initiation or termination of odor sampling, but
their pattern of activity across trial types reflected the matchi
non-match judgment. Furthermore, matchinon-match cells
fired differentially on S + versus S - trials in which the behavioral response was constant (R +), indicating that the activity patterns of these cells could be dissociated from the
behavioral response and, indeed, demonstrated better recognition “performance” than that reflected in the animal’s
behavioral responses. These data are consistent with char-
331
acterizations of hippocampal neuronal activity in monkeys
and rats performing other recognition memory tasks (Sakurai,
1990a; Wilson et al., 1990). Combining the findings across
studies, the pattern of results indicates that hippocampal cellular activity in recognition memory is best characterized as
reflecting the active processing of cues resulting in a representation of the outcome of the matchinon-match comparison. Also, the product of this processing may in some cases
be passed back to cortical structures for long-term storage
(Otto et al., 1991) so that such representations may play a
role in recollections of the previous stimuli and the context
in which they were experienced (Eichenbaum et al., 1992b).
The hippocampus does not maintain active
memory representations in recognition tasks,
but processes comparisons between current
information and memory representations stored
elsewhere
The present data indicate that hippocampal cellular activity
does not participate in storage of memories for single stimulus
items, as assessed either in terms of a “passive” representation reflected in differential activity during the sampling of
novel versus familiar cues or in terms of an “active” representation that maintains a sensory-evoked neural response
through the memory delay. These findings are consistent with
results from other studies on hippocampal neurons and contrast with the reports on cells in neocortical and parahippocampal areas. With regard to “passive” memory representations, Brown and colleagues (Brown et al., 1987; Riches et
al., 1991) directly compared responses of hippocampal and
parahippocampal neurons in monkeys to repeated presentations of visual stimuli. They found that neurons in parahippocampal cortical areas responded maximally to novel stimuli
and exhibited lesser responses when stimuli were repeated,
whether or not there were intervening presentations of different stimuli. By contrast, no hippocampal neurons had differential responses to novel vs. familiar cues; they did, however, fire differentially when stimuli were presented as
sample or matchinon-match cues. Only in the case of responses to object-place combinations has preferential activity
for novel stimuli been observed in the hippocampus (Cahusac
et al., 1989; Rolls et al., 1989).
Neurons in some neocortical association areas also exhibit
differential re3ponses to novel stimuli, but the degree to
which this differential response pattern can sustain interference differs from that of the parahippocampal areas. For example, cells in inferotemporal cortex of monkeys, like those
in the parahippocampal areas, produce smaller responses to
particular familiar visual patterns and faces but, unlike parahippocampal cells, differential responses in most inferotemporal neurons are abolished after presentation of even a single
interfering item (Baylis and Rolls, 1987; Rolls et al., 1989);
inferotemporal cells are able to sustain this type of representation over intervening items only when the match stimulus
is included among a set of recognition choices presented immediately following the sample (Miller et al., 1991).
With regard to “active” memory representations, the present data and results from other studies on rats and monkeys
indicate that neither hippocampal nor parahippocampal neu-
332
HIPPOCAMPUS VOL. 2, NO. 3, JULY 1992
rons sustain stimulus-evoked responses across a memory
delay, in contrast to the findings on neocortical areas. Sakurai
(1990a; 1990b) observed that hippocampal neurons did not
fire preferentially during the delay phase of an auditory-cued
cDNM task but that, as in this study, they did fire differentially on match versus non-match trials. By contrast, cells
in auditory cortex had sustained firing for cues during the
memory delay. Neurons in parahippocampal cortex, like
those in auditory cortex and unlike hippocampal cells, fired
differentially to specific auditory cues, but these cells did not
sustain firing through the delay. Watanabe and Niki (1985)
and Cahusac et al. (1989) found hippocampal neurons that
fired selectively during the delay phase in monkeys performing a spatial DNMS task, but these cells had firing correlates
like those in this study: they did not demonstrate a pattern
of cue-elicited, delay-sustained firing as would be expected
if they were maintaining an active representation of the sample cue. An appropriate interpretation of the observed delayrelated activity is that the cells were likely firing in association
with unidentified spatial or behavioral events that occurred
consistently during the intertrial interval. By contrast, several
investigations have shown that neurons in prefrontal and inferotemporal cortex of monkeys sustain sensory-elicited responses during the delay period of recognition memory tasks
(e.g., Kubota and Niki, 1971; Fuster, 1973; 1981; Miyashita
and Chang, 1988; cf. Goldman-Rakic et al., 1990).
Combining the findings across species on stimulus selectivity, “passive” and “active” memory representations, and
firing related to the outcome of matchhon-match comparisons, some tentative distinctions about the nature of recognition memory processing in different structures can be made;
these distinctions lead to an hypothesis about the interactive
processing of neocortical, parahippocampal, and hippocampal representations. First, neocortical association areas demonstrate highly selective sensory responses that are sustained
through delays in recognition memory tasks and show striking
differential responses to novel vs. familiar stimuli. These neocortical representations are, however, labile, in that they cannot be sustained across substantial perceptual interference.
Second, parahippocampal areas also demonstrate stimulus
selectivity, but, unlike the neocortex, these areas do not sustain an active representation in the absence of the stimulus.
They do, however, demonstrate a powerful passive representation, as reflected by differential activity for novel vs.
familiar cues. Also, in contrast to the neocortex, this passive
memory representation can sustain substantial interference.
Third, in distinction to both neocortical and parahippocampal
areas, the hippocampus (at least the CA1 area) demonstrates
stimulus selectivity for complex conjunctions of cues, but this
specificity is labile in that the nature of the correlate can
change dramatically across situations and therefore reflects
only abstracted relations among cues. The hippocampus
maintains neither active nor passive memory representations.
Instead, hippocampal activity reflects processing of the comparison between current and previous cues relevant to recognition performance.
Taking into account the well-documented reciprocal connections between the neocortex and parahippocampal areas,
and between parahippocampal areas and the hippocampus
(Amaral and Witter, 1989), a putative functional circuit for
interactions among these structures can be proposed. Specific perceptual representations can be sustained in the neocortex during relatively interference-free periods. These neocortical representations might support short-term recognition
and priming wherein the comparison between current and
stored representations is accomplished by a precise perceptual matching (Fuster and Jervey, 1973; Mikami and Kubota,
1980; Miller et al., 1991). Sensory processing also results in
a memory representation in the parahippocampal areas that
does not hold information by sustaining neural activity but
can maintain a longer-term and interference-insensitivetrace.
A perceptual matching process involving interactions between parahippocampal areas and the neocortex might subserve intermediate-term retention (Brown et al., 1987), accounting for the evidence that parahippocampal areas may
support DNMS performance even after hippocampal damage
(Murray and Mishkin, 1986; Zola-Morgan et al., 1989a). We
propose that the hippocampus does not maintain a representation of simple sensory cues, but receives and compares information about both current stimuli and representations of
previous stimuli maintained in the neocortex and/or parahippocampal areas. The nature of these comparisons is viewed
as different from the perceptual recognition processes characteristic of cortical areas, and likely includes, in the comparison of current and previous stimuli, rich contextual information that goes beyond the strict perceptual properties
upon which neocortical or parahippocampal matching is
based. The added predictive value derived from the outcomes
of such “declarative” processing constitutes the hippocampal contribution to recognition memory.
ACKNOWLEDGMENTS
Anne Blood and Richard Benoit assisted in the collection
of the data presented. Supported by NIH grant NS26402, NIA
grant AG09973, and NSF grant BNS-8810095 to H.E.
References
Aggelton, J. P., P. R. Hunt, and J. N. P. Rawlins (1986) The effects
of hippocampal lesions upon spatial and non-spatial tests of working memory. Behav. Brain Res. 19:133-146.
Aggleton, J. P., R. M. Nicol, A. E. Huston. and A. F. Fairbairn (1988)
The performance of amnesic subject on tests of experimental amnesia in animals: Delayed matching to sample and concurrent learning. Neuropsychologia 26:265-272.
Amaral, D. G., and M. P. Witter (1989) The three-dimensional organization of the hippocampal formation: A review of anatomical
data. Neuroscience 31:571-591.
Baylis, G. C., and E. T. Rolls (1987) Responses of neurons in the
inferior temporal cortex in short term and serial recognition memory tasks. Exp. Brain Res. 65:614-622.
Berger, T., B. Alger, and R. F. Thompson (1976) Neuronal substrate
of classical conditioning in the hippocampus. Science 192:483-485.
Brown, M. W. (1982) Effect of context on the response of single units
recorded from the hippocampal region of behaviourally trained
monkeys. In Neuronal Plasticity and Memory Formation, C. A.
Marsan and H. Matthies, eds., pp. 557-573 Raven, New York.
Brown, M. W., F. A. W. Wilson, and I. P. Riches (1987) Neuronal
evidence that inferomedial temporal cortex is more important than
hippocampus in certain processes underlying recognition memory.
Brain Res. 409:158-162.
Cahusac, P. M. B., and Y. Miyashita (1988) Hippocampal activity
HIPPOCAMPUS AND DELAYED NON-MATCH TO SAMPLE / Otto and Eichenbaum
related to the processing of single sensory-motor associations. Neurosci. Lett. 90:265-272.
Cahusac, P. M. B., Y. Miyashita, and E. T. Rolls (1989) Responses
of hippocampal formation neurons in the monkey related to delayed
spatial response and object-place memory tasks. Behav. Brain Res.
33:229-24O.
Clower, R. P., P. Alvarez-Royo, S . Zola-Morgan, and L. R. Squire
(1991) Recognition memory impairment in monkeys with selective
hippocampal lesions. SOC.Neurosci. Abstr. 17:338.
Eichenbaum, H., 1). Pettijohn, A. M. Deluca, and S. L . Chorover
(1977) Compact miniature microelectrode-telemetry system. Physiol. Behav. 18:1175-1178.
Eichenbaum, H., M. Kuperstein, A. Fagan, and J. Nagode (1987)
Cue-sampling and goal approach correlates of hippocampal unit
activity in rats performing an odor discrimination task. J. Neurosci.
7:716-732.
Eichenbaum, H., and N. J. Cohen (1988) Representation in the hippocampus: What do the neurons code‘? Trends Neurosci. 11:244248.
Eichenbaum, H., N. J. Cohen, T. Otto, and C. G. Wible (1992a)
Memory representation in the hippocampus: Functional domain
and functional organization, In Memory: Organization and Locus
ofchange, L. R. Squire, G. Lynch, N. M. Weinberger, and J. L .
McGaugh, eds., Oxford University Press, New York (in press).
Eichenbaum, H., T. Otto, and N. J. Cohen (1992b) The hippocampus:
What does it do? Behav. Neural Biol. 57:2-36.
Foster, T. C., E. P. Christian, R. Hampson, K. A. Campbell, and S.
A. Deadwyler (1986) Sequential dependencies regulate sensory
evoked responses of single units in the rat hippocampus. Brain Res.
4O8:86-96.
Fuster, J. M. (1973) Unit activity in prefrontal cortex during delayedresponse performance: Neuronal correlates of transient memory.
J. Neurophysiol. 36:61.
Fuster, J. M., and J. P. Jervey (1981) lnferotemporal neurons distinguish and retain behaviourally relevant features of visual stimuli.
Science 219:952-955.
Gaffan, D. (1974) Recognition impaired and association intact in the
memory of monkeys after transection of the fornix. J. Comp. Physiol. Psychol. 86: 1100-1 109.
Goldman-Rakic, P. S.,S. Funahashi, and C. J. Bruce (1990) Neocortical memory circuits. In Cold Spring Harbor Symposia on
Quantitative Biology, Vol. 55, The Brain pp. 1025-1038, Cold
Spring Harbor Laboratory Press, Plainview, N.Y..
Halgren, E. (1991) Firing of human hippocampal units in relation to
voluntary movements. Hippocampus 1:153-162.
Halgren, E., T.L. Babb, and P. H. Crandal(1978) Activity of human
hippocampal formation and amygdala neurons during memory testing. Electroencephalogr. Clin. Neurophysiol. 45585-601.
Kubie, J. L. (1984) A driveable bundle of microwires for collecting
single-unit data from freely moving rats. Physiol. Behav. 32: 115118.
Kubota, K., and H. Niki (1971) Prefrontal cortical unit activity and
delayed alternation performance in monkeys. J. Neurophysiol.
34:337.
Mikami, A , , and K. Kubota (1980) Inferotemporal neuron activities
and color discrimination with delay. Brain Res. 182:65-78.
Miller, E. K., L. Li, and R. Desimone (1991) A neural mechanism
for working and recognition memory in inferior temporal cortex.
Science 254: 1377-1379.
Mishkin, M. (1978) Memory in monkeys severely impaired by combined but not separate removal of the amygdala and hippocampus.
Nature 273:297-298.
Mishkin, M., and J. Delacour (1975) An analysis of short-term visual
memory in the monkey. J. Exp. Psychol. [Anim. Behav.] 1:326334.
Miyashita, Y., and H. S. Chang (1988) Neuronal correlate of pictoral
333
short-term memory in the primate temporal cortex. Nature 331:6870.
Miyashita, Y., E. T. Rolls, P. M. B. Cahusac, H. Niki, and J. D.
Feigenbaum (1989) Activity of hippocampal formation neurons in
the monkey related to a conditional spatial response task. J. Neurosci. 61:669-678.
Muller, R. U . , and J. L. Kubie (1987) The effects of changes in the
environment on the spatial firing of hippocampal complex spike
cells. J. Neurosci. 7:1951-1968.
Mumby, D. G.,J. P. Pinel, and E . R. Wood (1990) Nonrecurringitems delayed nonmatching-to-sample in rats: A new paradigm for
testing nonspatial working memory. Psychobiol. 18:321-326.
Murray, E. A., and M. Mishkin (1986) Visual recognition in monkeys
following rhinal cortical ablations combined with either amygdalectomy or hippocampectomy. J . Neurosci. 6:1991-2003.
O’Keefe, J., and L. Nadel (1978) The Hippocampus as a Cognitive
M a p . Oxford University Press, Oxford.
O’Keefe, J., and D. H. Conway (1978) Hippocampal place units in
the freely moving rat: Why they fire when they fire. Exp. Brain
Res. 31:573-590.
O’Keefe, J., and A. Speakman (1987) Single unit activity in the rat
hippocampus during a spatial memory task. Exp. Brain Res. 68: 127.
Ono, T., K. Nakamura, M. Fukuda, and R. Tamura (1991) Place
recognition responses of neurons in monkey hippocampus. Neurosci. Lett. 121:194-198.
Otto, T., and H. Eichenbaum (1992) Complementary roles of orbital
prefrontal cortex and the hippocampal system in an odor-guided
delayed non-matching to sample task. Behav Neurosci (in press).
Otto, T., H. Eichenbaum, S. I. Wiener, and C. G. Wible (1991) Learning-related patterns of CAI spike trains parallel stimulation parameters optimal for inducing hippocampal long-term potentiation.
Hippocampus 1:181-192.
Quirk, G . J., R. U . Muller, and J. L. Kubie (1990) The firing of
hippocampal place cells in the dark depends on the rat’s recent
experience. J. Neurosci. 10:2008-2017.
Ranck, J. B., Jr. (1973) Studies on single neurons in dorsal hippocampal formation and septum in unrestrained rats. Part I. Behavioral correlates and firing repertoires. Exp. Neurol. 41:461-531.
Riches, I. P., F. A. W. Wilson, and M. W. Brown (1991) The effects
of visual stimulation and memory on neurons of the hippocampal
formation and the neighboring parahippocampal gyms and inferior
temporal cortex of the primate. J. Neurosci. 11:1763-1779.
Rolls, E. T.,G. C. Baylis, M. E. Hasselmo, and V. Nalwa (1989)
The effect of learning on the face selective responses of neurons
in the cortex in the superior temporal sulcus of the monkey. Exp.
Brain Res. 76:153-164.
Rolls, E. T., Y. Miyashita, P. M. B. Cahusac, R. P. Kesner, H. Niki,
H., J . D. Feigenbaum, and L . Bach (1989) Hippocampal neurons
in the monkey with activity related to the place in which a stimulus
is shown. J. Neurophysiol. 9: 1835-1845.
Rothblat, L. A.. and L. F. Kromer (1991) Object recognition memory
in the rat: The role of the hippocampus. Behav. Brain Res. 42:2532.
Sakurai, Y. (1990a) Cells in the rat auditory system have sensorydelay correlates during the performance of an auditory working
memory task. Behav. Neurosci. 104:856-868.
Sakurai, Y . (1990b) Hippocampal cells have behavioral correlates
during the performance of an auditory working memory task in the
rat. Behav. Neurosci. 104:253-263.
Scoville, W. B., and B. Milner (1957) Loss of recent memory after
bilateral hippocampal lesions. J. Neurol. Neurosurg. Psychiatry
2O:ll-12.
Squire, L . R., J. G. Ojemann, F. M. Miezin, S. E. Petersen, T. 0.
Videen, and M. E. Raichle (1992) Activation of the hippocampus
334
HZPPOCAMPUS VOL. 2, NO. 3, JULY 1992
in normal humans: A functional anatomical study of memory. Proc.
Natl. Acad. Sci. 89:1837-1841.
Squire, L. R., and S. Zola-Morgan (1991) The medial temporal lobe
memory system. Science 253:1380-1386.
Squire, L. R., S. Zola-Morgan, and K. S. Chen(1988) Human amnesia
and animal models of amnesia: Performance of amnesic patients
on tests designed for the monkey. Behav. Neurosci. 102:210-221.
Watanabe, T., and H. Niki (1985) Hippocampdl unit activity and delayed response in the monkey. Brain Res. 325:241-254.
Wible, C. G., R. L. Findling, M. Shapiro, E. J. Lang, S. Crane, and
D. S. Olton (1986) Mnemonic correlates of unit activity in the hippocampus. Brain Res. 399:97-110.
Wiener, S. I., C. A. Paul, and H. Eichenbaum (1989) Spatial and
behavioral correlates of hippocampal neuronal activity. J. Neurosci. 9:2737-2763.
Wilson, F. A. W., I. P. Riches, and M. W. Brown (1990) Hippocampus and medial temporal cortex: neuronal activity related to behavioural responses during the performance of memory tasks by
primates. Behav. Brain Res. 40:7-28.
Zola-Morgan, S., L . R. Squire, and D. G. Amaral(1989a) Lesions of
the amygdala that spare adjacent cortical regions do not impair
memory or exacerbate the impairment following lesions of the hippocampal formation. J. Neurosci. 9:1922-1936.
Zola-Morgan, S., L. R. Squire, and D. G. Amaral. (1989b) Lesions
of the hippocampal formation but not lesions of the fornix or mammillary nuclei produce long-lasting memory impairment in the monkey. J. Neurosci. 9:898-913.